SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

This sections contains articles submitted by site users and articles imported from other sites on analytics

Aiming to Become A Data Scientist? Read This!

Data Sciences is a very vast field and in recent times, there is a high demand of professionals in this field. Dealing with data is not easy. Data sets available with companies are very large and to extract meaningful data is a tough job. Thus, the job of data scientist is becoming very important for decision-making and is based on automation and machine learning. The main role of data scientist is to organize and analyse data. Other than this, data can help in predictions, pattern detection analysis etc. All this can be done the help of some software which is specially designed for the task. The responsibilities of data scientist begin with data collection and ends with decision making on the basis of data.

To know more about the key roles of data scientist, requirements and skills visit: https://www.cio.com/article/3217026/data-science/what-is-a-data-scientist-a-key-data-analytics-role-and-a-lucrative-career.html#tk.cio_rs

 

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Dealing with Predictive Analytics Challenges

One of the most trending and look for technology, Predictive Analysis is a powerful tool that can help us to forecast and predict what lies ahead us. However, it is usually accompanied by few issues that user encounters while using it. They might not be visible during early stages of development but they can become great concern when they will not be able to deliver results to customer. Prevention is always better than cure and thus it is recommended to study the technology well before use. 

Following are few tips that one should use to avoid and resolve common project challenges:

  1. Create and execute a formal strategy
  2. Ensure data quality
  3. Manage data volume
  4. Respect data privacy and ownership
  5. Maximize usability
  6. Control costs
  7. Choose the right tools

    To read more about them visit: https://www.cio.com/article/3287937/predictive-analytics/7-tips-for-overcoming-predictive-analytics-challenges.html?upd=1532674958240

     

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AI Contributing Towards Medicine

Artificial Intelligence is spreading its wings and is coming into rescue in various fields. One such field which comes into rescue for humans is the health care sector. Combination of these two fields can bring great advancement in health care sector. Artificial Intelligence and Machine learning have already come into action in medicine. Following are the top 4 applications:

    1. Diagnosing Diseases: Not all diseases can easily be rectified. This could be time consuming and expensive. Here, various Deep Learning algorithms prove to be a solution. This focus on automatic diagnosis, making diagnosis much cheaper and accessible. 
    2. Developing Drugs Faster: Drug development is a time taking and a tedious task. It involves analytics and various rounds of testing. AI has already aced in speeding up the process.
    3. Personalizing Treatment: Same medical procedure can not be carried out on every patient. Choosing the course of treatment can be a difficult and a great responsibility. Machine Learning can automate this task. It can help in designing the right treatment plan.
    4. Improving Gene Editing: This is a technique that relies on targeting and editing specific location on the DNA. A careful selection needs to be made. Machine Learning models have successfully been able to predict target and effects successfully.

To read more at https://towardsdatascience.com/artificial-intelligence-in-medicine-1fd2748a9f87

 

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How big data can help in customer service domain?

In every enterprise the customer care services are the most essential part because it not satisfies the customers but it also leads to more productivity. To build the customer loyalty and drive your business to heights it’s important to care the customer service domain. Services of new customer care software platform which involves big data has took this domain to a new level.

For more information go to:

https://www.analyticsinsight.net/big-data-in-customer-support-delivering-values/

 

 

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AI based First Forex trading robot

Foreign exchange market is the word which is enough capable to draw attention of many people. Some people treat it as a fast money making technique while some people says it’s a way to enter the gambling world. Foreign exchange market is just a virtual platform which involves trading of different currencies. So what forex trading is? How AI and robotics can be involved in trading? What actually forex robots can do?

Want to know? Visit:

http://bigdata-madesimple.com/ai-driven-forex-trading-robot-first-kind/

 

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How to become a data scientist?

Data science comes with a new era on IT industries. From AI, ML, big datadata analytics and many more data science is proving its importance. With the emerging business plans on big data the requirement and demands of data scientists are also getting higher. Here are the guidelines to the students who want to pursue data science as their career. 

 Education background should relate to computer science.

 Beginning of your career experience and work focus

 Learning opportunities and certification

 Mid-career experience and certification

 Data science expertise and professionalism

For more details, visit:

https://www.analyticsinsight.net/how-to-become-a-data-scientist-the-skills-certifications-and-education-required-for-the-trendy-job/

 

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How AI and ML can contribute towards developing an intelligent cloud?

With reference to the aura spread by artificial intelligence and machine learning every enterprise is making their ideas with the relevance of these two giants. We are aware of the concept of cloud computing that it provides the storage and networking space over the internet which eventually reduces human efforts and cost. This sounds absolutely awesome. But what’s next? Can cloud be developed as “Intelligent Cloud”? Introducing the union of AI, ML and cloud, this will definitely raise the standards of cloud computing in future. The intelligent cloud will have the ability to learn from the enormous amount of data, builds up predictions accordingly and end up analyzing situations. This platform seems to perform tasks with high speed and provides greater efficiency. 

https://www.analyticsinsight.net/developing-intelligent-cloud-with-artificial-intelligence-and-machine-learning/

 

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How Artificial Intelligence is helping in startup plans?

Since last few years many startups has come up with some fantastic ideas which expands the scope of AI all over the world. Indians are also implementing various brilliant ideas of AI in their business startups. Here is the list of top 10 AI based startup plans which are leading the race.

1) Vernacular.ai: build multi-lingual chatbots for businesses

2) Fablulyst: helps all the online shoppers to buy based on their inputs.

3)  Artivatic data labs: helps large businesses and developers to come up with intelligent products and solutions with minimal development time and efforts.

4) Arya.ai: assists people in their daily core tasks

5) TAO automation: provides automated consultation which helps people in further optimization process.

6) Box.ai: build up a product which is capable of solving various analytics problems.

7) AskArvi: smart personal insurance platforms

8) ThirdWatch: E-commerce fraud-prevention platform

9) Embibe : educational startup, uses self-learning algorithm and machine learning

10) Mad Street Den: improve retail experience all over the world.

 

For more information go to:

https://www.analyticsinsight.net/10-hot-indian-artificial-intelligence-startups-to-watch-out-in-2018/

 

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How ActiveOps is securing G-cloud for betterment digital operation management?

ActiveOps is one of the leading providers of digital operation management, but somehow it couldn’t find any place to store G-cloud data with security. But now ActiveOps has come up with G-cloud 10 framework which assures and deliver greater efficiency and productivity by combining software and services.The G-cloud is made up with the ideology that most of the public sector can have the maximum advantages of cloud based automated services with more groundwork and prognostication.

https://www.analyticsinsight.net/activeops-secures-g-cloud-status-first-time-bringing-digital-operations-management-uk-public-sector/

 

 

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Few Softwares to Simplify GST

The herculean task of shifting to the new digital regime of taxation is making the country abuzz with the over explosion of information. This has mostly bewildered the entrepreneurs and SMEs as to how to make a business compliant to GST. Few GST compliant software solutions that can be used by a GST-ready entrepreneur are listed below.

·         CLEAR GST SOLUTION BY CLEARTAX- Priced at Rs. 10,000, the first cost effective well built cloud GST solution software released by Cleartax solutions is Clear GST. However it has few weaknesses including the need for separate accounting software for financial statements, is useful for small businesses only, no availability of offline backup and so on.

·         TALLY ERP 9 BY TALLY SOLUTIONS- Priced from Rs. 18000 to Rs. 54000(GST feature free if already having a license), Tally ERP 9 will be easier and more delightful to use than others with the only weakness of having no basic accounting system of debit and credit.

·         GEN-GST BY SAG INFOTECH- Priced at Rs. 2500, this software is different from others in the sense that it is available on all platforms like desktop, cloud, SAAS and so on. Some of its weaknesses involve its application to small businesses and need for separate accounting software for financial statements.

·         PWC INDIA- A GST solution with end-to-end automation aimed at helping companies to become GST compliant has been recently launched by PWC, the company which targets big business corporations instead of people.

Read more at: https://www.entrepreneur.com/article/297307

 

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Hybrid Cloud Model and its Applicability in Healthcare Organizations

Adopting a hybrid cloud model, a cloud computing environment using a mix of private cloud, third party public cloud services and on premises, has significant benefits if used in healthcare organizations. It not only allows them to take advantages of existing IT services and quick scaling out new resources but also ties various systems together for a seamless end-user experience. Moreover the journey towards the cloud does not need a complete infrastructural haul. However when considering a transition to a hybrid cloud model, the IT decision-makers should think through several considerations including leader requirements for shifts in culture, licensing, processes, system and host of other issues. Few tips for any healthcare organization to smoothen the path towards a hybrid cloud model are listed as follows:

·         Assessing and evaluating the cost-saving structure specific to the healthcare organization.

·         Identifying with the effects of cloud control and its management.

·         Preparing beforehand for impacts on the Service-Level Agreements.

·         Maintaining Software Licensing Compliance.

·         Proper Skills Developing to Support the New IT Environment.

·         Preparing Healthcare Staffs for Cultural Shifts.

Read more at: https://healthtechmagazine.net/article/2018/07/6-tips-smooth-your-move-hybrid-healthcare-cloud

 

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Big Data: A goldmine for automotive industry

As per the reports by SNS Telecom & IT, Big Data investment will cross $3.3 Billion by the end of 2018. Real time and historic data is rapidly gaining attraction towards diverse range and various sectors. There are many key findings in the report generated by SNS which ensures the widening scope of Big Data. 

For detailed information, visit:

https://www.analyticsinsight.net/big-data-3-3-billion-opportunity-automotive-industry-says-sns-telecom/

 

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How AI is a blessing to all the organization?

We are aware of the spells by AI in changing the appearance of business process both online as well as offline. AI has replaced many human functions in the industry through automated systems in field of communication and answering phone calls, emails etc. Technology giants such as Microsoft, Google, Amazon are investing their more power, time and money in strengthening their AI sector. So how AI is helping these organizations?

   Want to know, visit: 

https://www.analyticsinsight.net/why-artificial-intelligence-is-a-goldmine-to-an-organisation/

 

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How deep learning is a benefaction for police?

Investigation is crucial part for police because it only helps to catch the real criminal. But after collecting all the evidences and information, the case becomes more difficult to figure out as each information tells a different story. Nowadays when technology is on the peak of its uses, deep learning is giving its contribution by helping police through video footage analysis. Videos gathered from different number of sources are analyzed by a smart software which implements algorithms of deep learning for detection. Want to know, how it works? Visit: 

https://www.analyticsinsight.net/deep-learning-is-a-blessing-to-police-for-investigations/

 

 

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Real time challenges that needs to be overcome while implementing big data

It’s a difficult approach when it comes to the adoption of analytics facing real time challenges. It’s tough to analyze big data and assemble it in a single row. There are times when the minutes and seconds count are very crucial and no delays can be accepted. With the demand of more precision and accuracy we just cannot avoid the risk presence while accessing the data. But real time analytics demand much of our efforts and hard work to overcome the challenges and get that precision.  

For more details, visit: 

https://www.analyticsinsight.net/planning-to-embrace-big-data-here-are-real-time-challenges-you-might-face/

 

 

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Expanding the scope of data access across the organization

We are aware of stepping up standards of AI and its importance for data scientists. But, we cannot resist AI to limit its scope till technology only. With the advances, AI is setting its root in business organizations too. AI as a business tool comes up with many advantages to expand data access.

For more information, visit:

https://www.analyticsinsight.net/not-just-for-the-data-scientists-the-need-to-expand-data-access-across-the-organization/

 

 

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Being Smart with Embedded Analytics

Embedded Analytics helps in improving the revenue figures, user engagement and impart value to software applications by using the reporting and analytical capabilities in businesses. It helps businesses with precise decisions. Business operations coupled with embedded analytics allows for efficient process analysis and improving operations based on real-time situations. Predictive Analysis is the basis for operational decisions and embedded analytics used to make the results of predictive analytics is of the greatest value. People across an organization could use sophisticated analytics output which enables them to question the data. Putting the business intelligence platform inside the application architecture, embedded analytics guide users to choose where in the process the analytics is to be embedded. Integrated with CRM, ERP and financial systems, embedded analytics access core enterprise data and provide accurate information and further helps in reducing the cost. Lying at the roots of a radical revolution, analytics, or embedded analytics to be precise, would help companies accommodate the values to be provided to the end users.

Read More at: https://www.analyticsinsight.net/how-is-embedded-analytics-transforming-organizations-into-smart-enterprises/

 

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Contribution of AI: The Augmented Reality Microscope (ARM)

Artificial Intelligence has spread to almost all major and minor sectors and has been growing exponentially over the past few years. With the medical breakthrough in 2017 of AI identifying arrhythmia, researchers have developed microscopes for real-time diagnosis of cancer in 2018. It involved remodelling a standard microscope with deep neural networks integrating augmented reality giving a tool what is termed as the Augmented Reality Microscope. In such a microscope, a neural network is integrated for detection of tumor once the biopsy is conducted. Here, the eyepiece plays the role of the eye, AR is the 3-D image captured (which is the Field of View) and the role of the brain is played by the network. The output of the network is in the form of a heatmap which depicts the probability of cancer at each pixel location. The ARM has to its name a number of benefits like low equipment cost, low latency and also keeps pace with semi-continuous movements of the slide thus improving the accuracy of quantitative tissue assessments. With this we are ARM-ed well to fight against the unfortunate and sometimes catastrophic disease called cancer.

Read More at: https://www.analyticsinsight.net/augmented-reality-microscope-to-detect-cancer-cells/

 

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Asia gears up to be the global AI hub

AI has made it completely impeccable, from archaic development to cutting-edge technologies, reaching out to every niche possible, bearing the embryo of a heated competition between China and the US to revolutionize; the two major hubs having AI development in boon. Among the others following in this race include Singapore, Vietnam, Indonesia and Thailand. Vietnam has successfully implemented a crop intelligence system named Sero, that enables farmers to identify sick crops. Once enhanced further, Sero would assist in diagnosis and possible future treatments. An Indonesian telecom operator, Telkomsel, employed only chatbots to deal with clients and answer most of their queries. Sooner or later AI is digging deep roots in the industry although it takes some time for AI developers to present the desired results to the companies.

Read More at: https://www.analyticsinsight.net/asia-accelerates-growth-global-artificial-intelligence-industry/

 

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Benefits of Big Data in Fintech Services

The ways in which financial enterprises operate today have changed fundamentally due to technological evolutions. Titanic amount of data gathered from individuals’ electronic devices can be analyzed and used by the Fintech sector to deliver reliable services to its clients. Big data have been offering numerous benefits to this industry in areas of fraud detection, customer segmentation, risk management etc. Big data helps financial enterprises understand the transaction pattern of clients and can inform them about suspicious transactions. Big data also partially, if not fully, rules out the potential threats from bad investments and bad payers. Fintech companies aim at creating personalized financial services and big data assists in doing so by meeting the specific demands of the final customers. Big data also leads to better compliance capabilities ultimately translating into better services for both B2C and B2B consumers.

Read More at: https://www.smartdatacollective.com/fintech-big-data-play-role-financial-evolution/

 

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